TY - JOUR
T1 - The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates
AU - Bergeron, Lucie A.
AU - Besenbacher, Søren
AU - Turner, Tychele N.
AU - Versoza, Cyril J.
AU - Wang, Richard J.
AU - Price, Alivia Lee
AU - Armstrong, Ellie
AU - Riera, Meritxell
AU - Carlson, Jedidiah
AU - Chen, Hwei Yen
AU - Hahn, Matthew W.
AU - Harris, Kelley
AU - Kleppe, April Snøfrid
AU - López-Nandam, Elora H.
AU - Moorjani, Priya
AU - Pfeifer, Susanne P.
AU - Tiley, George P.
AU - Yoder, Anne D.
AU - Zhang, Guojie
AU - Schierup, Mikkel H.
N1 - Publisher Copyright:
© 2022, eLife Sciences Publications Ltd. All rights reserved.
PY - 2022/1
Y1 - 2022/1
N2 - In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a “Mutationathon”, a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.
AB - In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a “Mutationathon”, a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.
UR - http://www.scopus.com/inward/record.url?scp=85123676566&partnerID=8YFLogxK
U2 - 10.7554/eLife.73577
DO - 10.7554/eLife.73577
M3 - Article
C2 - 35018888
AN - SCOPUS:85123676566
SN - 2050-084X
VL - 11
JO - eLife
JF - eLife
M1 - e73577
ER -